Power Systems Research Scientist at Gridmatic

Job description

The Role We are looking for a Power Systems Research Scientist to develop physics-based models of large-scale transmission systems and their impact on electricity markets. You will work on large-scale optimization and simulation problems, including power flow, congestion, and security-constrained unit commitment and economic dispatch (SCUC/SCED). This role focuses on designing scalable algorithms and high-performance implementations for solving complex power system problems. This role sits at the core of our research and trading stack, building models and computational tools that directly impact how we understand and operate in electricity markets. We are particularly interested in rethinking power system optimization and simulation using modern computing (e.g., GPU acceleration). What you'll do: Develop and analyze power network models, including AC/DC power flow, contingency analysis, and security constraints Build and enhance large-scale optimization models (e.g., SCUC/SCED) with detailed transmission constraints Design and implement scalable algorithms and solver components for large-scale power system optimization Identify and address computational bottlenecks in network-constrained simulations and optimization Model and analyze congestion and transmission-driven market outcomes Simulate grid scenarios with high penetration of renewables, storage, and outages Collaborate with ML and trading teams to integrate network-aware signals into forecasting and decision systems Qualifications: Advanced degree (MS/PhD) in Electrical Engineering, Power Systems, or related field Strong background in power systems analysis and modeling Experience with power flow (AC/DC), transmission modeling, and congestion analysis Familiarity with ISO/RTO markets and network-constrained market outcomes Experience with optimization algorithms and large-scale mathematical programming Understanding of numerical methods for convex and/or non-convex optimization Strong programming skills in Python Nice to Have: Experience with tools such as PSS/E, PowerWorld, PSLF, or similar Familiarity with SCUC/SCED implementations Background in electricity market modeling or trading Experience working with large-scale datasets and cloud applications Familiarity with key power systems concepts such as PTDFs (power transfer distribution factors) and security constraints Experience with GPU-accelerated computing for large-scale optimization or simulation Experience with frameworks such as PyTorch or JAX for high-performance numerical computing Taking care of you today: - Continuing Education Opportunities - Flexible PTO - Medical, Dental and Vision plans with competitive employer contributions - Pre-Tax commuter benefits - $1500/year non profit donation matching program through Millie - Home Office Stipend Protecting your future for you and your family: - 401K contribution match up to 4% - Company-paid parental leave - Company Paid Life Insurance - Stock Option Loan Program Pay range $175,000 — $270,000 USD

Requirements

Must-haves

We are looking for a Power Systems Research Scientist to develop physics-based models of large-scale transmission systems and their impact on electricity markets.
This role sits at the core of our research and trading stack, building models and computational tools that directly impact how we understand and operate in electricity markets.
We are particularly interested in rethinking power system optimization and simulation using modern computing (e.g., GPU acceleration).
Develop and analyze power network models, including AC/DC power flow, contingency analysis, and security constraints
Build and enhance large-scale optimization models (e.g., SCUC/SCED) with detailed transmission constraints
Design and implement scalable algorithms and solver components for large-scale power system optimization
Identify and address computational bottlenecks in network-constrained simulations and optimization
Model and analyze congestion and transmission-driven market outcomes
Simulate grid scenarios with high penetration of renewables, storage, and outages
Collaborate with ML and trading teams to integrate network-aware signals into forecasting and decision systems
Advanced degree (MS/PhD) in Electrical Engineering, Power Systems, or related field
Strong background in power systems analysis and modeling
Experience with power flow (AC/DC), transmission modeling, and congestion analysis
Familiarity with ISO/RTO markets and network-constrained market outcomes
Experience with optimization algorithms and large-scale mathematical programming
Understanding of numerical methods for convex and/or non-convex optimization
Strong programming skills in Python

Nice-to-haves

Experience with tools such as PSS/E, PowerWorld, PSLF, or similar
Familiarity with SCUC/SCED implementations
Background in electricity market modeling or trading
Experience working with large-scale datasets and cloud applications
Familiarity with key power systems concepts such as PTDFs (power transfer distribution factors) and security constraints
Experience with GPU-accelerated computing for large-scale optimization or simulation
Experience with frameworks such as PyTorch or JAX for high-performance numerical computing

Application prep

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Keywords to mirror

mlpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Parental Leave